Introduction to NLTK

Description

Learn the basics of natural language processing with NLTK, the Natural Language ToolKit. First we'll cover tokenization, stemming and wordnet. Next we'll get into part-of-speech tagging, chunking & named entity recognition. Then we'll close with text classification and sentiment analysis. You'll walk out with new super-powers and an appreciation of the difficulties of analyzing human language.

Abstract

This tutorial will be a hands on approach to learning natural language processing using NLTK, the Natural Language ToolKit. We will cover everything from tokenizing sentences to phrase extraction, from splitting words to training your own text classifiers for sentiment analysis. Please come prepared with NLTK already installed so we can dive into the code & data immediately.

Hour 1: Tokenization, Stemming & Corpora

Tokenization & familiarity with corpus readers and models are required knowledge before you can get into the more interesting aspects of NLTK. This first hour will include:

an overview of modules & data

loading pickled models

sentence & word tokenization

stemming & lemmatization

an overview wordnet and other included corpora

Hour 2: Part-of-Speech Tagging & Chunking/NER

Using tokenization and a working knowledge of corpus readers & pickled models, we'll dive into part-of-speech tagging and chunking/NER, including: